Apple agreed to pay $95 million in cash to settle a proposed class action alleging its Siri assistant violated users' privacy by recording private conversations after accidental activations and sharing them with third parties.

The preliminary settlement was filed in Oakland federal court and needs approval from US District Judge Jeffrey White. The class period runs from 17 September 2014 to 31 December 2024, and members may receive up to $20 per Siri-enabled device, with the class estimated in the tens of millions. Apple denied wrongdoing. A parallel suit over Google's Voice Assistant, brought by the same plaintiffs' firms, is pending in the same district.

The Treasury rule implementing Executive Order 14105 — 31 CFR Part 850, published at 89 FR 90398 — became effective on 2 January 2025. It bars or requires notification for certain US-person investments in Chinese, Hong Kong and Macau companies working on semiconductors and microelectronics, quantum information technologies, and artificial intelligence, the three sectors the order designated as national-security technologies.

Law-firm analyses of the regime circulated that week as the compliance date hit.

President Vladimir Putin ordered Russia's government and its largest bank, Sberbank, to build cooperation with China in artificial intelligence.

The instructions were published on the Kremlin website as sanctions pressure continues to limit Russian access to Western AI hardware and models.

Nvidia completed its acquisition of Israeli AI infrastructure startup Run:ai after the European Commission granted unconditional approval earlier in December. The Commission had initially said the deal would require EU clearance and warned it could threaten competition in GPU-related markets.

Run:ai said it plans to make its GPU-virtualization and scheduling software open source so it can extend beyond Nvidia GPUs to the wider AI ecosystem. Nvidia holds roughly 80% of the AI GPU market.

DeepSeek released DeepSeek-V3 with downloadable weights, and the analysis ran through the New Year week. The specification: 671B total parameters with 37B activated per token, a 128K context window, pre-trained on 14.8 trillion tokens using multi-head latent attention, DeepSeekMoE and an auxiliary-loss-free load-balancing strategy.

The report's own framing is that it outperforms other open-source models and achieves performance comparable to leading closed-source models, and that the final training run needed only 2.788M H800 GPU-hours — the number behind the widely cited ~$5.6M compute estimate. Code is MIT-licensed; the weights ship under DeepSeek's own model license.